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Number-plate-detection-using-CNN

This program uses convolutional neural networks to recognize the text in the number plate.This network is based on this paper by Stark et al, which describes how google broke their own CAPTCHA system. Do check it out, as it gives more specifics about the architecture used than Google's paper.

To use this project:

  1. ./extractbgs.py SUN397.tar.gz: Extract ~3GB of background images from the SUN database into bgs/. (bgs/ must not already exist.) The tar file (36GB) can be downloaded here. This step may take a while as it will extract 108,634 images.

  2. ./gen.py 1000: Generate 1000 test set images in test/. (test/ must not already exist.) This step requires UKNumberPlate.ttf to be in the fonts/ directory, which can be downloaded here.

  3. ./train.py: Train the model. A GPU is recommended for this step. It will take around 100,000 batches to converge. When you're satisfied that the network has learned enough press Ctrl+C and the process will write the weights to weights.npz and return.

  4. ./detect.py in.jpg weights.npz out.jpg: Detect number plates in an image.